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Growth boundary of Fusarium graminearum spores as a function of temperature, pH, and H2S based on neural network

文献类型：期刊论文

作者Zhu, Yan1,2; Gao, Yameng1; Wang, Wenke1,2; Kan, Wenjie1,2; Tang, Caiguo1; Wu, Lifang1,2
刊名FOOD BIOSCIENCE
出版日期2024-10-01
卷号61
关键词Fusarium graminearum spores Environmental factors Growth limits Neural network
ISSN号2212-4292
DOI10.1016/j.fbio.2024.104797
通讯作者Tang, Caiguo(cgtang@ipp.ac.cn) ; Wu, Lifang(zy624@mail.ustc.edu.cn)
英文摘要Fusarium graminearum (F. graminearum) poses a substantial threat to global food security, with its impact closely linked to environmental conditions. This study aims to anticipate F. graminearum spore growth across diverse environments and assess alterations in the fungistatic capacity of hydrogen sulfide (H2S) gas in response to environmental variations. The experimental data, namely spore germination ratios, are monitored and recorded at hourly intervals across 100 permutations comprising four distinct temperature levels, five varying pH values, and five diverse concentrations of H2S. The investigation integrates three environmental factors as input variables, utilizing a feedforward neural network to establish growth boundaries based on spore germination ratios. The accuracy of models at various stages-training, validation, and testing-is evaluated using a confusion matrix. Logistic regression models are employed for effectiveness comparison with neural networks. Results indicate that neural networks successfully predict F. graminearum spore germination events. Notably, H2S does not influence the temperature preferences of spores. Temperature has a more substantial impact on the fungistatic ability of H2S compared to pH. The study reveals the adaptability of F. graminearum spores to adverse conditions over time. This research delves into temperature, pH, and H2S synergistic effects on spore germination, contributing to predictive models for F. graminearum and enhancing our understanding of how environmental factors regulate its growth.
WOS关键词HEAD BLIGHT ; GERMINATION ; SURVIVAL ; DYNAMICS
资助项目National Key Research and Development Program of China[2022YFD2301403] ; National Natural Science Foundation of China[32201760] ; Major Special Project of Anhui Province[2021d06050003] ; Hefei Institutes of Physical Science ; Chinese Academy of Sciences (CASHIPS) Director's Fund[YZJJKX202201] ; Students' Innovation and Entrepreneurship Foundation of USTC[CY 2023S008]
WOS研究方向Food Science & Technology
语种英语
WOS记录号WOS:001294936700001
出版者ELSEVIER
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; Major Special Project of Anhui Province ; Hefei Institutes of Physical Science ; Chinese Academy of Sciences (CASHIPS) Director's Fund ; Students' Innovation and Entrepreneurship Foundation of USTC
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/136082]  
专题中国科学院合肥物质科学研究院
通讯作者Tang, Caiguo; Wu, Lifang
作者单位1.Chinese Acad Sci, Hefei Inst Phys Sci, Ctr Ion Beam Bioengn & Green Agr, Hefei 230031, Anhui, Peoples R China
2.Univ Sci & Technol China, Sch Life Sci, Hefei 230027, Anhui, Peoples R China
推荐引用方式
GB/T 7714		 Zhu, Yan,Gao, Yameng,Wang, Wenke,et al. Growth boundary of Fusarium graminearum spores as a function of temperature, pH, and H2S based on neural network[J]. FOOD BIOSCIENCE,2024,61.
APA Zhu, Yan,Gao, Yameng,Wang, Wenke,Kan, Wenjie,Tang, Caiguo,&Wu, Lifang.(2024).Growth boundary of Fusarium graminearum spores as a function of temperature, pH, and H2S based on neural network.FOOD BIOSCIENCE,61.
MLA Zhu, Yan,et al."Growth boundary of Fusarium graminearum spores as a function of temperature, pH, and H2S based on neural network".FOOD BIOSCIENCE 61(2024).

入库方式： OAI收割

来源：合肥物质科学研究院

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